Literature DB >> 18411967

A more rational approach to new-product development.

Eric Bonabeau1, Neil Bodick, Robert W Armstrong.   

Abstract

Companies often treat new-product development as a monolithic process, but it can be more rationally divided into two parts: an early stage that focuses on evaluating prospects and eliminating bad bets, and a late stage that maximizes the remaining candidates' market potential. Recognizing the value of this approach, Eli Lilly designed and piloted Chorus, an autonomous unit dedicated solely to the early stage. This article demonstrates how segmenting development in this way can speed it up and make it more cost-effective. Two classes of decision-making errors can impede NPD, the authors say. First, managers often ignore evidence challenging their assumptions that projects will succeed. As a result, many projects go forward despite multiple red flags; some even reach the market, only to fail dramatically after their introduction. Second, companies sometimes terminate projects prematurely because people fail to conduct the right experiments to reveal products' potential. Most companies promote both kinds of errors by focusing disproportionately on late-stage development; they lack the early, truth-seeking functions that would head such errors off. In segmented NPD, however, the early-stage organization maintains loyalty to the experiment rather than the product, whereas the late-stage organization pursues commercial success. Chorus has significantly improved NPD efficiency and productivity at Lilly. Although the unit absorbs just one-tenth of Lilly's investment in early-stage development, it delivers a substantially greater fraction of the molecules slated for late Phase II trials--at almost twice the speed and less than a third of the cost of the standard process, sometimes shaving as much as two years off the usual development time.

Entities:  

Mesh:

Year:  2008        PMID: 18411967

Source DB:  PubMed          Journal:  Harv Bus Rev        ISSN: 0017-8012


  6 in total

Review 1.  How to improve R&D productivity: the pharmaceutical industry's grand challenge.

Authors:  Steven M Paul; Daniel S Mytelka; Christopher T Dunwiddie; Charles C Persinger; Bernard H Munos; Stacy R Lindborg; Aaron L Schacht
Journal:  Nat Rev Drug Discov       Date:  2010-02-19       Impact factor: 84.694

Review 2.  Lessons from 60 years of pharmaceutical innovation.

Authors:  Bernard Munos
Journal:  Nat Rev Drug Discov       Date:  2009-12       Impact factor: 84.694

Review 3.  A decade of innovation in pharmaceutical R&D: the Chorus model.

Authors:  Paul K Owens; Eyas Raddad; Jeffrey W Miller; John R Stille; Kenneth G Olovich; Neil V Smith; Rosie S Jones; Joel C Scherer
Journal:  Nat Rev Drug Discov       Date:  2014-12-15       Impact factor: 84.694

Review 4.  Product Development: From Concept to Market.

Authors:  Faryan Jalalabadi; Aryan Sameri; Edward M Reece
Journal:  Semin Plast Surg       Date:  2018-10-22       Impact factor: 2.314

5.  A qualitative exploration of early assessment of innovative medical technologies.

Authors:  Iben Fasterholdt; Anne Lee; Kristian Kidholm; Knud Bonnet Yderstræde; Kjeld Møller Pedersen
Journal:  BMC Health Serv Res       Date:  2018-11-06       Impact factor: 2.655

6.  Application of machine learning to predict reduction in total PANSS score and enrich enrollment in schizophrenia clinical trials.

Authors:  Jagdeep T Podichetty; Rebecca M Silvola; Violeta Rodriguez-Romero; Richard F Bergstrom; Majid Vakilynejad; Robert R Bies; Robert E Stratford
Journal:  Clin Transl Sci       Date:  2021-05-03       Impact factor: 4.689

  6 in total

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